| Title: |
Quantitative Model for Choosing Programming Language for Online Instruction |
| Language: |
English |
| Authors: |
Sherman, Steven J., Shehane, Ronald F., Todd, Dewey W. |
| Source: |
Journal of Instructional Pedagogies. May 2018 20. |
| Availability: |
Academic and Business Research Institute. 147 Medjool Trail, Ponte Vedra, FL 32081. Tel: 904-435-4330; e-mail: editorial.staff@aabri.com; Web site: http://www.aabri.com |
| Peer Reviewed: |
Y |
| Page Count: |
16 |
| Publication Date: |
2018 |
| Document Type: |
Journal Articles
Reports - Descriptive |
| Education Level: |
Higher Education |
| Descriptors: |
Programming Languages, Online Courses, Computer Science Education, Business Administration Education, Models, Selection Tools, Selection Criteria |
| ISSN: |
2327-5324 |
| Abstract: |
Colleges are increasingly offering online courses, including computer programming courses for business school students. Programming languages that are most useful to students are those that are widely used in the job market. However, the most popular computer languages change at least every three years. Therefore, the language used for instruction in a business programming course must be re-evaluated regularly. This paper establishes a quantitative model for choosing the best language for an online business programming course. Factors considered in the quantitative model include platform compatibility, marketability of the language, object-oriented programming support, availability of an interactive development environment, and the availability of interactive online teaching tools and videos. The paper next presented an example of the quantitative model used for selecting a language for a new online business programming course at a selected university. The final section of the paper presents the results and conclusions of the analysis. [Note: The volume number (19) shown on the PDF is incorrect. The correct citation is v20 May 2018.] |
| Abstractor: |
As Provided |
| Number of References: |
61 |
| Entry Date: |
2018 |
| Accession Number: |
EJ1178734 |
| Database: |
ERIC |
